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Machine Learning Engineer, Computer Vision
Machine Learning Engineer, Computer VisionMetropolis Technologies • Seattle, WA, United States
Machine Learning Engineer, Computer Vision

Machine Learning Engineer, Computer Vision

Metropolis Technologies • Seattle, WA, United States
Hace 9 días
Tipo de contrato
  • A tiempo completo
Descripción del trabajo

Machine Learning Engineer, Computer Vision

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout‑free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout‑free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable – giving us back our most valuable asset, time.

As a Machine Learning Engineer at Metropolis, you will accelerate recognition commerce through data innovation. You will be a key leader in Engineering, responsible for designing and building the robust generative data engine and intelligent algorithms that fuel our ML models. Your mission is to bridge data and models through automation, creating the scalable foundation that underpins the predictive, personalized experiences defining the future of the built world.

What you'll do

  • Work with the machine learning team to perform state‑of‑the‑art research, train, and optimize machine learning algorithms
  • Design, implement, and maintain active learning algorithms and generative vision models to ensure cost efficient data sampling and learning
  • Maintain and revisit innovative methodologies to curate high quality data and annotations
  • Design, implement, and maintain the machine learning data pipelines and infrastructure
  • Work with technologies like AWS, SQL / NoSQL databases, Kafka, Airflow, and NVIDIA Triton, ensuring efficient and effective use of these tools
  • Collaborate with other Engineering and Product teams to define requirements and facilitate the smooth deployment of software into production
  • Play a vital role in the entire development lifecycle, from concept and requirement identification to implementation
  • Implement best practices in automation, testing, and deployment to foster rapid feature / model development and release
  • Foster a culture that views bugs and production issues as opportunities for improvement
  • Contribute to the hiring and cultural development within Metropolis Engineering
  • Ensure high availability and scalability of Machine Learning systems
  • Collaborate with partners to integrate their products seamlessly into the Metropolis platform

What we're looking for

  • MS or PhD in Computer Science, Engineering, or a related field, or equivalent work experience
  • 3+ years of experience in machine learning and software engineering, with expertise in computer vision and multi‑modal models
  • Proficiency in Python and Machine Learning frameworks (PyTorch / TensorFlow / ONNX / TensorRT)
  • Strong experience with cloud services, preferably AWS
  • Familiarity with Machine Learning model serving infrastructure and best practices
  • Knowledge of transactional and analytical database technologies
  • Strong understanding of the agile development process and CI / CD pipelines and tools (e.g., Github Actions, Jenkins)
  • Excellent communication skills, capable of presenting complex technical information clearly
  • Additional skills (not required but a plus)

  • Experience in high‑growth, innovative environments
  • When you join Metropolis, you’ll join a team of world‑class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows.

    The anticipated base salary for this position is $150,000.00 USD to $180,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant’s qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and / or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short‑term and long‑term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more.

    Metropolis values in‑person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office‑first model, which requires employees to be on‑site at least four days a week, fostering organic interactions that spark creativity and connection.

    Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting.

    As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.

    Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.

    Seniority level

    Mid‑Senior level

    Employment type

    Full‑time

    Job function

    Engineering and Information Technology

    Industries

    Consumer Services and Facilities Services

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